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• Programming_with_Big_Data_in_R abstract "Programming with Big Data in R (pbdR) is a series of R packages and an environment for statistical computing with Big Data by using high-performance statistical computation. The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical software. The significant difference between pbdR and R code is that pbdR mainly focuses on distributed memory systems, where data are distributed across several processors and analyzed in a batch mode, while communications between processors are based on MPI that is easily used in large high-performance computing (HPC) systems. R system mainly focuses on single multi-core machines for data analysis via an interactive mode such as GUI interface.Two main implementations in R using MPI are Rmpi and pbdMPI of pbdR. The pbdR built on pbdMPI uses SPMD parallelism where every processor is considered as worker and owns parts of data. The SPMD parallelism introduced in mid 1980 is particularly efficient in homogeneous computing environments for large data, for example, performing singular value decomposition on a large matrix, or performing clustering analysis on high-dimensional large data. On the other hand, there is no restriction to use manager/workers parallelism in SPMD parallelism environment. The Rmpi uses manager/workers parallelism where one main processor (manager) servers as the control of all other processors (workers). The manager/workers parallelism introduced around early 2000 is particularly efficient for large tasks in small clusters, for example, bootstrap method and Monte Carlo simulation in applied statistics since i.i.d. assumption is commonly used in most statistical analysis. In particular, task pull parallelism has better performance for Rmpi in heterogeneous computing environments.The idea of SPMD parallelism is to let every processor do the same amount of work, but on different parts of a large data set. For example, a modern GPU is a large collection of slower co-processors that can simply apply the same computation on different parts of relatively smaller data, but the SPMD parallelism ends up with an efficient way to obtain final solutions (i.e. time to solution is shorter). It is clear that pbdR is not only suitable for small clusters, but is also more stable for analyzing Big data and more scalable for supercomputers. In short, pbdR does not like Rmpi, snow, snowfall, do-like, nor parallel packages in R, does not focus on interactive computing nor master/workers, but is able to use both SPMD and task parallelisms.↑ ↑ ↑ 3.0 3.1 ↑ ↑".
• Programming_with_Big_Data_in_R influencedBy C_(programming_language).
• Programming_with_Big_Data_in_R influencedBy Fortran.
• Programming_with_Big_Data_in_R influencedBy Message_Passing_Interface.
• Programming_with_Big_Data_in_R influencedBy R_(programming_language).
• Programming_with_Big_Data_in_R license GNU_General_Public_License.
• Programming_with_Big_Data_in_R license Mozilla_Public_License.
• Programming_with_Big_Data_in_R thumbnail Pbdr.png?width=300.
• Programming_with_Big_Data_in_R wikiPageExternalLink HighPerformanceComputing.html.
• Programming_with_Big_Data_in_R wikiPageExternalLink RBigData.
• Programming_with_Big_Data_in_R wikiPageExternalLink REU2013Team1.pdf.
• Programming_with_Big_Data_in_R wikiPageExternalLink REU2013Team2.pdf.
• Programming_with_Big_Data_in_R wikiPageExternalLink pbdRtara2013.pdf.
• Programming_with_Big_Data_in_R wikiPageExternalLink r-at-12000-cores.
• Programming_with_Big_Data_in_R wikiPageExternalLink www.r-pbd.org.
• Programming_with_Big_Data_in_R wikiPageID "39775648".
• Programming_with_Big_Data_in_R wikiPageRevisionID "636739269".
• Programming_with_Big_Data_in_R date "October 2014".
• Programming_with_Big_Data_in_R designer "Wei-Chen Chen, George Ostrouchov, Pragneshkumar Patel, and Drew Schmidt".
• Programming_with_Big_Data_in_R developer "pbdR Core Team".
• Programming_with_Big_Data_in_R influencedBy "R, C, Fortran, and MPI".
• Programming_with_Big_Data_in_R latestTestVersion "Through GitHub at RBigData".
• Programming_with_Big_Data_in_R license "General Public License and Mozilla Public License".
• Programming_with_Big_Data_in_R logo "200".
• Programming_with_Big_Data_in_R name "pbdR".
• Programming_with_Big_Data_in_R operatingSystem Cross-platform.
• Programming_with_Big_Data_in_R paradigm "SPMD and MPMD".
• Programming_with_Big_Data_in_R text "snow, snowfall, do-like,".
• Programming_with_Big_Data_in_R typing Type_system.
• Programming_with_Big_Data_in_R website www.r-pbd.org.
• Programming_with_Big_Data_in_R year "Sep. 2012".
• Programming_with_Big_Data_in_R subject Category:Cross-platform_free_software.
• Programming_with_Big_Data_in_R subject Category:Data-centric_programming_languages.
• Programming_with_Big_Data_in_R subject Category:Data_mining_and_machine_learning_software.
• Programming_with_Big_Data_in_R subject Category:Free_statistical_software.
• Programming_with_Big_Data_in_R subject Category:Functional_languages.
• Programming_with_Big_Data_in_R subject Category:Numerical_analysis_software_for_Linux.
• Programming_with_Big_Data_in_R subject Category:Numerical_analysis_software_for_OS_X.
• Programming_with_Big_Data_in_R subject Category:Numerical_analysis_software_for_Windows.
• Programming_with_Big_Data_in_R subject Category:Parallel_computing.
• Programming_with_Big_Data_in_R subject Category:Programming_languages.
• Programming_with_Big_Data_in_R subject Category:Statistical_software.
• Programming_with_Big_Data_in_R type ProgrammingLanguage.
• Programming_with_Big_Data_in_R type Software.
• Programming_with_Big_Data_in_R type Work.
• Programming_with_Big_Data_in_R type CreativeWork.
• Programming_with_Big_Data_in_R type InformationEntity.
• Programming_with_Big_Data_in_R type Thing.
• Programming_with_Big_Data_in_R type Q386724.
• Programming_with_Big_Data_in_R type Q7397.
• Programming_with_Big_Data_in_R type Q9143.
• Programming_with_Big_Data_in_R comment "Programming with Big Data in R (pbdR) is a series of R packages and an environment for statistical computing with Big Data by using high-performance statistical computation. The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical software.".
• Programming_with_Big_Data_in_R label "Programming with Big Data in R".
• Programming_with_Big_Data_in_R sameAs m.0w3311s.
• Programming_with_Big_Data_in_R sameAs Q16975325.
• Programming_with_Big_Data_in_R sameAs Q16975325.
• Programming_with_Big_Data_in_R wasDerivedFrom Programming_with_Big_Data_in_R?oldid=636739269.
• Programming_with_Big_Data_in_R depiction Pbdr.png.
• Programming_with_Big_Data_in_R homepage www.r-pbd.org.
• Programming_with_Big_Data_in_R isPrimaryTopicOf Programming_with_Big_Data_in_R.
• Programming_with_Big_Data_in_R name "pbdR".
• Programming_with_Big_Data_in_R page www.r-pbd.org.